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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Role of Nonequilibrium Solvent Effects in Enhancing Direct CO 2 Capture at the Air–Aqueous Amino Acid Interface

Direct air capture (DAC) technologies are limited by the poor understanding of the dynamic role of interfaces in modulating the chemisorption of CO 2 from air into solutions. While the reactivity of aqueous amine-based solvents in the bulk environment is strongly inhibited by nonequilibrium solvent effects, promoting DAC at interfaces posits a possibility to reduce the coupling with the solvent and significantly accelerate DAC. Building on an experimentally proven concept to bring an anionic glycine absorbent to the interface through ion-pairing interactions with a positively charged surfactant, we establish the fundamental time scales for key elementary steps involved in DAC with rate theory and enhanced-sampling ab initio molecular dynamics simulations. Here, we elucidate the mechanism by which water influences the free energy barriers and dynamical crossing-recrossing of those barriers, affecting the reaction rates. We find that water reorganizes to partially dehydrate [-NH 2 ], facilitating S N 2-based CO 2 conversion to a zwitterion, which then releases a proton via overhydration of [-NH 2 ]. The low-density interfacial water favors dehydration over overhydration, leading to a comparatively higher barrier (slower kinetics) for proton release. The barrier-recrossing events neutralize this effect, letting both steps occur at the same time scale (sub-microseconds) and making the overall DAC process faster at the interface than in the bulk water. Such an understanding of environment-sensitive solvent effects on the reaction kinetics will help design tailored interfaces for enhanced CO 2 capture kinetics via control of solvation and ion paring.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Mean force emission theory for classical bremsstrahlung in strongly coupled plasmas

This work presents mean force emission theory, which extends the classical theory of bremsstrahlung emission to strongly coupled plasmas. In the high-frequency limit, the theory reduces to solving for the electron trajectory during a binary collision, but where the electron–ion interactions occur through the potential of mean force. In the low-frequency limit, it uses an autocorrelation formalism that captures effects of multiple collisions and strongly correlated motion. The predictions are benchmarked by comparison with first-principles classical molecular dynamics simulations of a fully ionized hydrogen plasma in which all interactions are repulsive. The comparison shows good agreement up to Coulomb coupling strengths of Γ∼30. The theory improves upon traditional models by including strong coupling effects and systematically including the effect of multiple collisions. Furthermore, mean force emission theory provides evidence that the Drude correction factor commonly used in quantum calculations of optical quantities may not be adequate at strong coupling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Multistage nucleation pathway in LiF molten salt mirrors the crystal–melt interface structure

Despite over a century of studies, fundamental questions remain about the processes governing crystal nucleation from melts or solutions. Research over the past three decades has presented mounting evidence for kinetic pathways of crystal nucleation that are more complex than envisioned by the simplest forms of classical theory. Such observations have been presented for colloidal and elemental systems with covalent and metallic bonding. Despite the technological and geochemical importance of molten salts, similar studies for these ionically bonded systems are currently lacking. Here we develop a machine learning interatomic potential for a model ionic system: LiF. The potential features quantum-level accuracy for both liquid and multiple solid polymorphs over wide temperature and pressure ranges and accurately reproduces experimentally measured properties. Thanks to the efficiency of the potential, which enables microsecond-scale molecular dynamics simulations, induction times for nucleation of LiF solids from their melts are computed over a range of undercoolings. With the aid of a set of robust local order parameters established here, the simulations reveal that homogeneous crystal nucleation in undercooled melts preferentially initiates from liquid regions showing slow dynamics and high bond orientational order simultaneously, and the second-shell order of both precritical nuclei and the surface of postcritical nuclei is dominated by hexagonal close packing and body-centered cubic local structure, even though the nucleus core is dominated by face-centered cubic structure corresponding to the stable rocksalt crystal structure. Finally, we establish a connection between the crystallization pathway and the equilibrium crystal-melt interface structure.

Applied Physical Sciences↗
DOE OSTI2025

OpenFerro v0.1.0

OpenFerro is a Python package for on-lattice atomistic dynamics simulation of ferroic materials. OpenFerro is based on JAX, a high-performance linear algebra package supporting auto-differentiation and GPU acceleration. OpenFerro is designed to minimize the effort required to build on-lattice Hamiltonian models, and to perform molecular dynamics (MD) and Landau-Lifshitz-Gilbert simulations. Unlike existing codes, OpenFerro provides a unified interface to model different types of local order parameters.

Xie, Pinchen [Lawrence Berkeley National Laborator↗
DOE OSTI2024

Four-dimensional phase space tomography from one-dimensional measurements of a hadron beam

In this paper, we use one-dimensional measurements to infer the four-dimensional phase space density of an accumulated proton beam in the Spallation Neutron Source (SNS) accelerator. The reconstruction was performed by maximizing the distribution’s entropy subject to the measurement constraints and thus represents the most conservative inference from the data. The reconstructed distribution reproduces the measured profiles down to the noise level, and simulations indicate that the problem is reasonably well constrained. Similar measurements could serve as benchmarks for beam dynamics simulations in the SNS or hadron accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

A Solution Method for the Filtered Lifting Line Theory

The filtered lifting line theory presents a continuous form of the inviscid momentum equations of flow over a lifting device, such as a wing or rotor blade, using body forces without mathematical singularities. This theory is also consistent with an actuator line representation of a lifting device. In this work, we present a reformulation of the equations in terms of the local flow angle along the line, which allows solving the stand-alone equations using multivariate root-finding algorithms. This approach can be used to obtain a fast, computationally inexpensive solution of the loading distribution along a wing without the need to perform computational fluid dynamic simulations. We study the requirements in terms of resolution in the spanwise direction and establish the criteria for spacing and minimum amount of points required along the blade to obtain converged solutions. The solutions are compared to results from large-eddy simulations, and we observed excellent agreement with less than a percent difference in quantities along the blade between the methods.

17 WIND ENERGY↗
DOE OSTI2026

Elastic strain engineering of lattice thermal conductivity of silicon: An ab-initio study

Silicon (Si) is the most essential material in the semiconductor industry. It is important to manage the thermal properties of crystalline Si. Elastic strain engineering (ESE) has proven to be an effective tool in controlling the electrical conductivity of Si in strained-silicon technology; its effects on the thermal conductivity of silicon, therefore, warrants careful investigation. The ESE effect is much more pronounced for nanostructured materials due to the ultralarge elastic strains (on the order of 10%) achievable at the nanoscale. In this work, the lattice thermal conductivity (κ L ) of Si under hydrostatic, biaxial, and uniaxial strain states is studied with ab-initio simulations, and the values of strain-dependent κ L compare well with experimental results and existing molecular dynamics simulations. To understand the mechanisms of strain-modulated κ L , the phonon bands, scattering rate, and Grüneisen parameters of phonon modes are computed. It is shown that strain can significantly change the anharmonicity of the crystal system, thus changing phonon scattering rates and κ L . Our results demonstrate that ESE can reduce silicon κ L by up to approximately 90%. Furthermore, uniaxial and biaxial strains can induce highly anisotropic thermal conductivity in Si, with relative variations up to 58.5% and 14.5%, respectively.

Anisotropy in Thermal Conductivity↗
DOE OSTI2025

Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report

Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simulating Crystallization in a Colloidal System Using State Predictive Information Bottleneck Based Enhanced Sampling

Here, we investigate crystal nucleation in supersaturated colloid suspensions using enhanced molecular dynamics simulations augmented with machine learning techniques. The simulations reveal that crystallization in the model colloidal system studied here, with particles interacting through a repulsive screened Coulomb Yukawa potential, proceeds from vapor to dense liquid droplet to crystalline phases across multiple high barriers. Employing a one-dimensional reaction coordinate derived from the State Predictive Information Bottleneck framework, our simulations capture back-and-forth phase transitions across multiple barriers effectively in biased metadynamics simulations. We obtain relative free energy differences between different phases and also quantify the roles of different molecular level features in driving the phase changes.

Chemistry↗
DOE OSTI2024

Ultrafast electron diffraction of photoexcited gas-phase cyclobutanone predicted by ab initio multiple cloning simulations

We present the result of our calculations of ultrafast electron diffraction (UED) for cyclobutanone excited into the S2 electronic state, which is based on the non-adiabatic dynamics simulations with the Ab Initio Multiple Cloning (AIMC) method with the electronic structure calculated at the SA(3)-CASSCF(12,12)/aug-cc-pVDZ level of theory. The key features in the UED pattern were identified, which can be used to distinguish between the reaction pathways observed in the AIMC dynamics, although there is a significant overlap between representative signals due to the structural similarity of the products. The calculated UED pattern can be compared with the experiment.

Chemistry↗
DOE OSTI2025

Machine learning force field model for kinetic Monte Carlo simulations of itinerant Ising magnets

Here, we present a scalable machine learning (ML) framework for large-scale kinetic Monte Carlo (kMC) simulations of itinerant electron Ising systems. As the effective interactions between Ising spins in such itinerant magnets are mediated by conducting electrons, the calculation of energy change due to a local spin update requires solving an electronic structure problem. Such repeated electronic structure calculations could be overwhelmingly prohibitive for large systems. Assuming the locality principle, a convolutional neural network (CNN) model is developed to directly predict the effective local field and the corresponding energy change associated with a given spin update based on Ising configuration in a finite neighborhood. As the kernel size of the CNN is fixed at a constant, the model can be directly scalable to kMC simulations of large lattices. Our approach is reminiscent of the ML force field models widely used in first-principles molecular dynamics simulations. Applying our ML framework to a square-lattice double-exchange Ising model, we uncover unusual coarsening of ferromagnetic domains at low temperatures. Our work highlights the potential of ML methods for large-scale modeling of similar itinerant systems with discrete dynamical variables.

machine learning↗
DOE OSTI2025

Thermal-Fluid and Thermal-Structural Response of the T-Tube Modular Divertor to Spatiotemporally Varying Heat Loads

Tungsten (W) is the leading candidate for divertor target plates because of its high melting point (>3000°C), thermal conductivity, and ultimate tensile stress. While W and its alloys are the only solid materials that can survive the high heat fluxes incident on the divertor, W’s low-ductility high ductile-to-brittle transition temperature of ~600°C and relatively low recrystallization temperature (RT) of ~1300°C pose structural (among other) challenges. The objective of this work is to estimate the thermal-fluid and thermal-structural performance of the helium (He)-cooled T-tube divertor, which was originally developed by the Advanced Reactor Innovation and Evaluation Study (ARIES) using numerical simulations. Here, predictions of temperature distributions across the plasma-facing structural component and surface pressures from computational fluid dynamics simulations are used to determine stress distributions using commercial structural finite element modeling software over a range of fusion-relevant conditions. The maximum allowable incident heat fluxes are determined based on the temperature limits imposed by the ITER elastic Structural Design Criteria for In-vessel Components (SDC-IC) and the maximum RT over a range of He mass flow rates and presented in the form of performance design charts. Our recent work found that thermal- structural criteria accounting for the low ductility of W in a finger-type modular divertor constrain the maximum incident heat fluxes to values well below the ITER specifications, and those based on considering only the RT demonstrate that integrated thermal-fluid and elastic structural performance evaluation are required for accurate assessment of divertor performance. This novel analysis of the T-tube considers how nonuniform and transient incident heat fluxes affect its thermal-fluid and thermal-structural performance, as well as the effect of volumetric heating, which can be as great as 27% of the power incident on the divertor surface. The W tile of the T-tube, with its relatively large plasma-facing area of ~15 cm 2 , will likely experience significant spatial variations in incident heat flux. This work therefore assesses whether steady-state incident heat flux profiles with a peak of 10 MW/m 2 and maximum heat flux gradients of 200 MW/m 2 per m exceed the structural limits imposed by the ITER elastic SDC-IC and the maximum RT over a range of fusion-relevant conditions. The effect of transient heat fluxes typical of plasma detachment and reattachment from the target plate due, for example, to gas injection are also evaluated

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Hard–Soft Acid–Base Theory Explains Photoexcited Carrier Dynamics in Porphyrin/CNT Nanohybrids: Time-Domain Atomistic Analysis

We employ the fundamental chemical concepts of hard− soft acid−base to formulate general principles governing excited-state dynamics in zinc porphyrin (ZnP)/carbon nanotube (CNT) hybrids for energy photoconversion. Atomistic quantum dynamics simulations demonstrate that electron-withdrawing and donating substituents at the ZnP β-pyrrolic position strongly influence the dynamics. ZnP photoexcitation produces subpicosecond electron transfer (ET) from ZnP to CNT, in agreement with the experiment. Substitutions of CN by H and tBu accelerate the ET. The trend is directly related to the hard−soft acid−base concept because the soft−soft interaction between the t Bu- ZnP acid and the mild CNT base enhances the donor−acceptor coupling. Longer coherence and more active vibrational modes facilitate the ET in t Bu-ZnP/CNT. Electron−hole recombination in CN-ZnP/CNT occurs on a hundred picosecond time scale, nicely corroborated by the experiment. The exciton lifetime is extended beyond a nanosecond by the substitutions. The soft−soft interaction in t Bu-ZnP/ CNT increases the splitting between the highest occupied orbitals of the two subsystems, reduces their mixing, and decreases nonadiabatic coupling between the ground and excited states. Rapid decoherence and involvement of low-frequency vibrations favor longer lifetimes. Our investigation reveals that larger p K a of the β-pyrrolic acid gives rapid ET and slow recombination and provides detailed mechanistic information, essential for future optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Bayesian blacksmithing: discovering thermomechanical properties and deformation mechanisms in high-entropy refractory alloys

Finding alloys with specific design properties is challenging due to the large number of possible compositions and the complex interactions between elements. This study introduces a multi-objective Bayesian optimization approach guiding molecular dynamics simulations for discovering high-performance refractory alloys with both targeted intrinsic static thermomechanical properties and also deformation mechanisms occurring during dynamic loading. The objective functions are aiming for excellent thermomechanical stability via a high bulk modulus, a low thermal expansion, a high heat capacity, and for a resilient deformation mechanism maximizing the retention of the BCC phase after shock loading. Contrasting two optimization procedures, we show that the Pareto-optimal solutions are confined to a small performance space when the property objectives display a cooperative relationship. Conversely, the Pareto front is much broader in the performance space when these properties have antagonistic relationships. Density functional theory simulations validate these findings and unveil underlying atomic-bond changes driving property improvements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Elucidating the Role of Hydrogen at c‐In 2 O 3 /a‐In 2 O 3− x Interface

Ab initio molecular dynamics simulations and hybrid functional electronic structure calculations are employed to determine the formation, the structural and electronic properties, and the dynamics of covalent (In—OH) and ionic (In—H—In) hydrogen defects at crystalline-In 2 O 3 /amorphous-In 2 O 3−x interface. This comprehensive computational study considers (i) various interstitial and substitutional hydrogen site locations within the crystalline, amorphous, and interfacial regions; (ii) several oxygen-to-hydrogen ratios; and (iii) possible defect charged states. The results reveal hydrogen's inability to fully passivate the undercoordinated under-shared in atoms in amorphous highly substoichiometric oxide, giving rise to the formation of deep electron traps even in net-charge neutral structures. These trap defects are found to be sensitive to photoexcitation, in contrast to In—OH with H's electronic states located below the valence band and to In—H—In, where H is found to maintain its charge state upon illumination. Nevertheless, H plays a critical role in photoinduced conductivity and its relaxation by promoting In—O coordination transformations at the interfacial region, including deterioration of the crystalline layer. Finally, the results help identify mobile H species and metastable H defect complexes (such as In—H—H—In, In—OH–H—In, and In—OH–O—In) that are responsible for long relaxation times of the conductivity decay.

H defects↗
DOE OSTI2025

Dynamics and activation of membrane-bound B cell receptor assembly

B-cell receptor (BCR) complexes are expressed on the surface of a B-cell and are critical in antigen recognition and modulating the adaptive immune response. Even though the relevance of antibodies has been known for almost a hundred years, the antigen-dependent activation mechanism of B-cells has remained elusive. Several models have been proposed for BCR activation, including cross-linking, conformation-induced oligomerization, and dissociation activation models. Recently, the first cryo-EM structures of the human B-cell antigen receptor of the IgM and IgG isotypes have been published that validates the asymmetric organization of the BCR complex. Here, we carry out extensive molecular dynamics simulations to probe the conformational changes upon antigen binding and the influence of the membrane lipids. We identify two critical dynamical events that could be associated with antigen-dependent activation of BCR. First, antigen binding causes increased flexibility in regions distal to the antigen binding site. Second, antigen binding alters the rearrangement of IgM transmembrane helices, including the relative interaction of Igα/Igβ that mediates intracellular signaling. Furthermore, these transmembrane rearrangements lead to changes in localized lipid composition. Our work indirectly supports the conformational-change induced models of BCR activation and contributes to the understanding of the antigen-dependent activation mechanism of BCRs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tracking surface charge dynamics on single nanoparticles

Surface charges play a fundamental role in physics and chemistry, in particular in shaping the catalytic properties of nanomaterials. However, tracking nanoscale surface charge dynamics remains challenging due to the involved length and time scales. Here, we demonstrate time-resolved access to the nanoscale charge dynamics on dielectric nanoparticles using reaction nanoscopy. We present a four-dimensional visualization of the spatiotemporal evolution of the charge density on individual SiO 2 nanoparticles under strong-field irradiation with femtosecond-nanometer resolution. The initially localized surface charges exhibit a biexponential redistribution over time. Our findings reveal the influence of surface charges on surface molecular bonding through quantum dynamical simulations. We performed semi-classical simulations to uncover the roles of diffusion and charge loss in the surface charge redistribution process. Understanding nanoscale surface charge dynamics and its influence on chemical bonding on a single-nanoparticle level unlocks an increased ability to address global needs in renewable energy and advanced health care.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Modeling Dust Production, Growth, and Destruction in Reionization-era Galaxies with the CROC Simulations. II. Predicting the Dust Content of High-redshift Galaxies

Abstract We model the interstellar dust content of the reionization era with a suite of cosmological, fluid-dynamical simulations of galaxies with stellar masses ranging from ∼10 5 to 10 9 M ⊙ in the first 1.2 Gyr of the Universe. We use a post-processing method that accounts for dust creation and destruction processes, allowing us to systematically vary the parameters of these processes to test whether dust-dependent observable quantities of galaxies at these epochs could be useful for placing constraints on dust physics. We then forward model observable properties of these galaxies to compare to existing data. We find that we are unable to simultaneously match existing observational constraints with any one set of model parameters. Specifically, the models that predict the largest dust masses D / Z ≳ 0.1 at z = 5—because of high assumed production yields and/or efficient growth via accretion in the interstellar medium—are preferred by constraints on total dust mass and infrared (IR) luminosities, but these models produce far too much attenuation in the ultraviolet (UV), preventing them from matching observations of β UV . To investigate this discrepancy, we analyze the relative spatial distribution of stars and dust as probed by IR and UV emission, which appear to exhibit overly symmetric morphologies compared to existing data, likely due to the limitations of the stellar feedback model used in the simulations. Our results indicate that the observable properties of the dust distribution in high redshift galaxies are a particularly strong test of stellar feedback.

79 ASTRONOMY AND ASTROPHYSICS↗